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11 to 20 of 834 Results
Jan 6, 2025
Zimmermann, Barbara, 2025, "Replication Data for: Quantifying large carnivore predation relative to human harvest on moose in an intensively managed boreal ecosystem", https://doi.org/10.18710/UWXPHW, DataverseNO, V1
This dataset contains the data and the code used to calculate moose density inside wolf territories and relates to the article entitled "Quantifying large carnivore predation on moose relative to human harvest in an intensively managed boreal ecosystem" and published in Ecologica...
Plain Text - 6.5 KB - MD5: cd6176671ae3abd0067496905bd50132
Readme-file containing a description of the data files and code.
Adobe PDF - 559.2 KB - MD5: 2a50a3f310d4d22f090db19dbd348e0b
Supplement 2 of related publication, including R-code to estimate moose abundance in wolf territories at start of study year.
Comma Separated Values - 1.6 KB - MD5: c9ec9e2fe71123652c875536f95177b1
Input data nr 1 used to estimate moose abundance in wolf territories
Comma Separated Values - 593 B - MD5: ef0d0cd871be3cb579aae280d2dde982
Input data nr 2 used to estimate moose abundance in wolf territories
Dec 12, 2024
Khatri, Shumaila; Sjølie, Hanne K.; Nyrud, Anders Q., 2024, "Replication Data for: Consumer drivers for intended adoption of recycled wood as construction material", https://doi.org/10.18710/BE5TXF, DataverseNO, V1
The data collection was conducted to find determinants that affect adoption of recycled wood in Norway. The data was collected during 15th Dec 2023 to 5th Jan 2024 by Norstat AS via online surveys. The two datasets represent cabin-owners (count = 446) and house-owners (count = 46...
Plain Text - 5.1 KB - MD5: 2f638185d0025e567f55d9c4e3d9e3ee
README file about data collection and variables.
Comma Separated Values - 13.5 KB - MD5: 6224d5c002df0a1859c0c7715909d5ae
Dataset from cabin-owners survey.
Comma Separated Values - 14.1 KB - MD5: 40fc1af967e308301adf9a408d27896e
Dataset from house-owners survey.
Plain Text - 1.0 KB - MD5: 0aefee838242ebebfa95717580969afe
Mplus codes for Model used in SEM.
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